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Usage Information

Engineering the gut microbiota to treat hyperammonemia
Ting-Chin David Shen, Lindsey Albenberg, Kyle Bittinger, Christel Chehoud, Ying-Yu Chen, Colleen A. Judge, Lillian Chau, Josephine Ni, Michael Sheng, Andrew Lin, Benjamin J. Wilkins, Elizabeth L. Buza, James D. Lewis, Yevgeny Daikhin, Ilana Nissim, Marc Yudkoff, Frederic D. Bushman, Gary D. Wu
Ting-Chin David Shen, Lindsey Albenberg, Kyle Bittinger, Christel Chehoud, Ying-Yu Chen, Colleen A. Judge, Lillian Chau, Josephine Ni, Michael Sheng, Andrew Lin, Benjamin J. Wilkins, Elizabeth L. Buza, James D. Lewis, Yevgeny Daikhin, Ilana Nissim, Marc Yudkoff, Frederic D. Bushman, Gary D. Wu
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Research Article Gastroenterology

Engineering the gut microbiota to treat hyperammonemia

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Abstract

Increasing evidence indicates that the gut microbiota can be altered to ameliorate or prevent disease states, and engineering the gut microbiota to therapeutically modulate host metabolism is an emerging goal of microbiome research. In the intestine, bacterial urease converts host-derived urea to ammonia and carbon dioxide, contributing to hyperammonemia-associated neurotoxicity and encephalopathy in patients with liver disease. Here, we engineered murine gut microbiota to reduce urease activity. Animals were depleted of their preexisting gut microbiota and then inoculated with altered Schaedler flora (ASF), a defined consortium of 8 bacteria with minimal urease gene content. This protocol resulted in establishment of a persistent new community that promoted a long-term reduction in fecal urease activity and ammonia production. Moreover, in a murine model of hepatic injury, ASF transplantation was associated with decreased morbidity and mortality. These results provide proof of concept that inoculation of a prepared host with a defined gut microbiota can lead to durable metabolic changes with therapeutic utility.

Authors

Ting-Chin David Shen, Lindsey Albenberg, Kyle Bittinger, Christel Chehoud, Ying-Yu Chen, Colleen A. Judge, Lillian Chau, Josephine Ni, Michael Sheng, Andrew Lin, Benjamin J. Wilkins, Elizabeth L. Buza, James D. Lewis, Yevgeny Daikhin, Ilana Nissim, Marc Yudkoff, Frederic D. Bushman, Gary D. Wu

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Usage data is cumulative from November 2025 through November 2026.

Usage JCI PMC
Text version 2,651 308
PDF 386 43
Figure 1,338 0
Supplemental data 175 3
Citation downloads 301 0
Totals 4,851 354
Total Views 5,205
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Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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Copyright © 2026 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

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